Atmospheric CompositionThere’s Something in the Air

Atmospheric CompositionAtmospheric CompositionComponent R&A Programs:

Upper Atmosphere Research Program (UARP)Ozone recovery; UT & stratosphere chemical / physicalprocess; Chemistry-Climate connections;

Radiation Sciences Program (RSP)Climate impacts of aerosols and clouds –aerosolmorphology & chemistry, convective transport, etc.

Tropospheric Chemistry Program (TCP)Transport and transformation of gases and aerosolsinfluencing Climate and Air Quality

Atmospheric Chemistry Modeling and Analysis Program (ACMAP)

Data analysis and modeling integrating satellite, aircraft,balloon, and ground-based observations

Observational Assets:

Satellites: Aura, CALIPSO, CloudSat, Terra,Aqua, Parasol, ENVISAT, ACE, EUMetSat, OCO,Glory, NPP, GOSAT

Aircraft: DC-8, WB-57F, ER-2, P-3B, UAVs, other agency and international aircraft

Balloons: High-Altitude/Heavy-Lift for remote sensing, in situ soundings for ozone, T, H2O,aerosols

Ground: AGAGE, NDAAC, AERONET, MPLNet,NATIVE, SMART-COMMIT, other agency networks

Other Investments: Laboratory studies, modeland instrument development

Key Roles played by NASA centers and non- NASA organizations

FY07 R&A Budget: $36.5M for ~250 tasks

~40% reduction in science-buying power from FY04

NASA NASAUniv.Univ.

OtherOGov

OtherOGov

Number of Funded Tasks

Allocation ofResearch Funds

Scientific Activities/Key Results in Air Quality

Satellites • Aura – Significant global observations connecting ozone chemistry, air quality, and climate• CALIPSO/CloudSat - Detailed vertical profiles of cloud and aerosol properties on a global scale• MODIS - Global coverage of areal distribution of clouds and aerosols• MISR - Global multi-angle measurements of the areal and vertical distribution of cloud and aerosol properties• MOPITT - Global observations of carbon monoxide quantifying anthropogenic and natural sources• Constellation Science - improve cross-platform opportunities for A-Train and International Constellation (CEOS)

Suborbital Field Campaigns for Science and Validation• INTEX-B/MILAGRO- Campaign examining North American inflow/outflow of pollution• Small-scale campaigns, i.e., IONS, EAST-AIRE, TexAQS/GoMACCS

Long-term Observation Networks for Science and Validation• AGAGE - Global network for tracking atmospheric burdens of Montreal and non-CO2 Kyoto Protocol gases• NDAAC - Remote-sensing research network for observing and understanding the physical / chemical state of the

stratosphere and UT to assess the impact of stratospheric changes on the troposphere and on global climate• AERONET - Global network of aerosol optical depth measurements for climate research and satellite validation• MPLNet - Network for aerosol and cloud vertical profile measurements for climate research and satellite validation

Modeling and Data Analysis• GEOS-Chem – Global tropospheric CTM playing a key role in the interpretation of NASA satellite data and used by over

30 research groups worldwide in a wide range of applications including chemistry/climate coupling• GOCART - Simulates aerosols and related species to analyze NASA observations for aerosol-climate studies• AC&C / Aerocom / CCMVAL - Continued intercomparison of models to validate and improve chemistry/climate

assessment and prediction

Coincident measurements of tropospheric ozone and carbon monoxide are critical for understanding chemical and dynamical processes. Note the tropical high ozone coincident with CO which is associated with biomass burning.

CCoincident measurements of tropospheric ozone and carbon monoxideoincident measurements of tropospheric ozone and carbon monoxide are critical for understanding chemical and dynamical processes.are critical for understanding chemical and dynamical processes. Note the Note the tropical high ozone coincident with CO which is associated with tropical high ozone coincident with CO which is associated with biomass biomass burning.burning.

Carbon MonoxideCarbon MonoxideOzoneOzone

Sum

mer

05

Sum

me r

05

F al l

0 5F a

l l 0 5

Win

ter 0

5 -0 6

Win

ter 0

5 -0 6

TES: Maps of Tropospheric Ozone & Carbon MonoxideTES: Maps of Tropospheric Ozone & Carbon MonoxideTES: Maps of Tropospheric Ozone & Carbon Monoxide

OMI & MLS produce a tropospheric ozone product by subtracting the MLS stratospheric ozone from OMI column ozone.

This can be compared to the more sparse but direct observations from TES

OMI & MLS produce a OMI & MLS produce a tropospheric ozone tropospheric ozone product by subtracting product by subtracting the MLS stratospheric the MLS stratospheric ozone from OMI ozone from OMI column ozone. column ozone.

This can be compared This can be compared to the more sparse but to the more sparse but direct observations direct observations from TESfrom TES

OMI & MLS: Global Tropospheric Ozone Residual

•• Daily monitoring of SODaily monitoring of SO22 emissions is emissions is possible with OMI.possible with OMI.

•• The Peruvian copper smelters are among The Peruvian copper smelters are among the worldthe world’’s largest industrial point sources of s largest industrial point sources of SOSO22 . .

Ecuador/S. Colombia volcanoes

Ilo copper smelter

La Oroya copper smelter

Ilo

La Oroya

CarnCarn et al.et al., in prep, in prep

PERU

Daily SODaily SO22 burdens for 3 source regionsburdens for 3 source regionsSept. 2004 Sept. 2004 -- June 2005June 2005

Average OMI SOAverage OMI SO22 vertical columnvertical columnSep 2004 Sep 2004 -- June 2005June 2005

OMI: SO2 emissions from smelters and volcanoesOMI: SO2 emissions from smelters and volcanoes

CALIPSO Observations CALIPSO Observations –– All 3 Lidar ChannelsAll 3 Lidar Channels

Desert dust

Biomass smoke

Cirrus

56.7132.16

47.8528.57

39.9225.78

31.9423.46

23.9321.42

15.9019.55

7.8117.77

-0.2316.05

-8.2814.23

-16.3112.56

-24.3310.69

-32.328.64

-40.276.30

Alti

tude

, km

Alti

tude

, km

Alti

tude

, km

Fire locations in southern Africa from MODIS

10 June 2006

9 June 2006

• Quantitatively calculate intercontinental transport of dust (Kaufman et al.,2005) or pollution (Yu et al. in preparation)

• Observationally-based estimate of aerosol direct radiative effect (Remer andKaufman, 2006; Yu et al., 2006; Bellouin et al.2005; Chung et al., 2005)

• Observationally-based estimate of oceanic aerosol anthropogenic component or direct forcing (Kaufman et al. 2006)

• Tool for operational air quality forecasts (Al Saadi et al. 2005)

MODIS Aerosol Products View the Global Aerosol System in an Entirely New Way

Aerosol Source Plume Physical CharacteristicsAerosol Source Plume Physical Characteristics from Spacefrom Space--based Multibased Multi--angle Imagingangle Imaging

R. Kahn, W-H Li, C. Moroney, D. Diner, J. Martonchik, and E. Fishbein, JGR 2007, in press

•

Wildfire smoke plumes tend to concentrate in layers of high relative atmospheric stabilitylayers of high relative atmospheric stability. •

With sufficient buoyancy from a fire or volcanofire or volcano, can they reach upper levelsupper levels

in the atmosphere.•

The measurements can be used directly in models that predict aerosol transportdirectly in models that predict aerosol transport, oras a guide for model aerosol vertical distributionmodel aerosol vertical distribution

where measurements are absent.

1

23

4

5

0.0 0.6 1.2 0.0 1.2 2.4 0 5000 10,0001

2

3

4

5

MISR nadir view

Oregon wildfire Sept 04 2003 Smoke & bkgd aerosol amount ~Particle Size Smoke Plume Height

0

2

4

6

8

10

0 2 4 6 8 10

Atmospheric Stability

P 1-2P 4-5

0 50 100

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Hei

ght (

km)

Number of Pixels

P1

0 100 200

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Hei

ght (

km)

Number of Pixels

P2

0 50 100

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Hei

ght (

km)

Number of Pixels

P3

0 50 100

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Hei

ght (

km)

Number of Pixels

P4

0 20 40 60

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Hei

ght (

km)

Number of Pixels

P5

MISR Stereo-Derived Smoke Plume Height histograms for five patches, plus model-derived atmospheric stability profile

.

The 2004 Alaska Fires

MOPITT 700 hPa CO mixing ratio for the period 15-23 July, 2004, during the INTEX-A field campaign. The intense wildfires in Alaska produced plumes of carbon monoxide pollution that can be traced across North America and the Atlantic Ocean.

.

MOPITT improves estimates for boreal fire emissions and their impact on CO and O3

Enhancements to CO column and surface O3 due to fires, July 15-25, 2004.

• Inverse modeling of MOPITT observations using the MOZART CTM showed that the fires emitted about as much CO as did human- related activities in the continental USA during the same time period, about 30 Tg CO June-August

• Because of the wildfires, ground-level concentrations of O3 increased by 25% or more in parts of the northern continental USA and by 10% as far away as Europe

Pfister et al., GRL, 2005

CO

O3

INTEX-B & MILAGRO: NASA Airborne Observations and Satellite Validation in 2006

INTEX- B Web Site http://cloud1.arc.nasa.gov/intex-b/ MILAGRO Web Site http://www.joss.ucar.edu/milagro/

• MILAGRO: March 2006- Mexico City during dry season- Megacity plume evolution

• INTEX-B: April-May 2006 - maximum Asian inflow to

North America- seasonal contrast

NSF C-130NASA DC-8

Goal: To understand the transport, transformation, & impacts of gases & aerosols on air quality & climate from local to global scales

MILAGRO

MCMA-2006

MIRAGE-Mex

MAX-Mex

INTEX-B/1INTEX-B/2 (IMPEX)ITOP

INTEX-B

Partners: NASA, NSF, DOE, US NGOs, MEX, CAN, GER; MEX NGOs

DLR FALCON DOE G-1 Canadian Cessna

UW DuchessNASA J-31NASA Be-200

INTEX-B Targeted Aura Satellite Validation Activities (CO, O3 , HCHO, NO2 , HNO3 , H2 O, HCN, Aerosol)

Aura

DC-8 C-130 3/4 3/9 3/12 3/16 3/19 3/21 4/17 4/23 4/25 4/26 4/30 5/4 5/7 5/9 5/12 4/24 4/28 5/1 5/3 5/8 5/11

TES* • • • • • • • • • • • • • OMI • • • • • • • • • • • • • HIRDLS# • • MLS • • Others** • • • • • • • • • • • • • • • * TES validation performed for both Nadir and Limb measurements # Night flights required for HIRDLS validation ** Mainly AIRS, SCIAMACHY and TERRA

March 2006 – MilagroIs there a Mexico-to-Houston

Ozone connection?

April-May 2006 – INTEX-BIs there an Asia-to-North

America Ozone connection?

August 2006 – TEXAQS-GOMACCSWhat is upwind-downwindof Houston Ozone?

Design raises traditional instrument to “state-of-art” toolfor integrating models, in-situ, satellite data

Strategic Strategic OzonesondeOzonesonde Networks Networks in Integrated Observationsin Integrated Observations

<http://croc.gsfc.nasa.gov/intexb/ions06.html><http://croc.gsfc.nasa.gov/intexb/ions06.html>

Tropospheric Ozone Budgets Computed Tropospheric Ozone Budgets Computed For Each IONS SoundingFor Each IONS Sounding

IONSIONS--04 Budgets:04 Budgets:25% from Stratosphere25% from Stratosphere15% RCL 15% RCL –– regional regional convection & lightningconvection & lightning10% 10% -- Boundary layer Boundary layer ––local pollutionlocal pollution50% 50% -- AdvectedAdvected fresh fresh and aged pollutionand aged pollution

Thompson et al., Thompson et al., JGR,JGR, 2007a,b2007a,b

Narragansett

01020304050607080

701

704

707

710

713

716

719

722

725

728

731

803

806

809

812

815

Days

Ozo

ne in

DU AD

STRCLBL (1km)

EAST-AIRE Observation

EASTEAST--AIRE experiment over NE China in April 2005AIRE experiment over NE China in April 2005 provide the first inprovide the first in--situ situ SOSO22 measurements to validate and improve AURA OMI by Flying measurements to validate and improve AURA OMI by Flying

American Instruments on a Chinese Aircraft for the first time inAmerican Instruments on a Chinese Aircraft for the first time in historyhistory

SO2

Aerosol

Aircraft spirals

Summary: Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Back trajectory Chemistry 2006090418NOy Emissions

O3 P-L

TEXAQS 2006 Ensemble Lagrangian Trajectory Analysis

SFC (red) and 850 (blue)

Enhanced regional ozone production was present 16% of days during the study in Houston and preceded 3 of the 6 periods of locally high O3

AGAGE is distinguished by its capability to measure over the globe at high frequency almost all of the important species in the Montreal Protocol to protect the ozone layer and almost all of the significant non-CO2 gases in the Kyoto Protocol to mitigate climate change.

Advanced Global Atmospheric Gases ExperimentThe Advanced Global Atmospheric Gases Experiment (AGAGE), and its predecessors (the Atmospheric Lifetime Experiment, ALE, and the Global Atmospheric Gases Experiment, GAGE) have been measuring the composition of the global atmosphere continuously since 1978.

The ALE/GAGE/AGAGE stations occupy coastal & mountain sites around the world chosen to provide accurate measurements of trace gases whose lifetimes are long compared to global atmospheric circulation times.

SOGE: System for Observation of Halogenated Greenhouse Gases in Europe.

NIES: National Institute for Environmental Studies, Japan.

SNU: Seoul National University, Korea.

AGAGE WEB SITE at http://agage.eas.gatech.edu

Priorities:• studying the temporal and spatial variability of atmospheric composition and structure• detecting trends in overall atmospheric composition and understanding their impacts on

the stratosphere and troposphere,• establishing links between climate change and atmospheric composition,• calibrating and validating space-based measurements of the atmosphere, • supporting process-focused scientific field campaigns, and• testing and improving theoretical models of the atmosphere.

JungfraujochJungfraujoch

Lauder, NZ S. Pole

OHP, France

Andoya, NorwayAndoya, Norway Mauna Loa, HIMauna Loa, HI

Network for the Detection of Atmospheric Composition Change:

Exploring the Interface Between ChangingAtmospheric Composition and Climate

AERONET-An Internationally Federated Network

• Aerosol Optical Properties Research & Enabling Project– Program of long term systematic network measurements– Homepage access http://aeronet.gsfc.nasa.gov/

• Mission Objectives– Validation of satellite aerosol retrievals – Characterization of aerosol optical properties– Synergism with satellite observations and climate models

Cooling

Heating

Hansen et al. 1997

The Dynamic Atmosphere:AERONET-Defining Aerosol Optical Properties

Micro-Pulse Lidar Network (MPLNET)

MPLNET Status E.J. Welton, NASA GSFC Code 613.1 04/24/07

Status:12 active sites6 planned sites (in preparation)6 proposed sites (funding dependent)

12 short-term field campaigns1 ocean cruise (two cruises pre-dating MPLNET are available)

Accomplishments:• MPLNET has generated and contributed to over 30 peer reviewed

publications since 2000.• Validation & algorithm development for ICESat & TOMS. CALIPSO pending.• Cooperation with AERONET, modeling, and satellite groups led to

formulation of new Synergy Tool (online aerosol database)

Goddard team + 13 Partners compose MPLNET:NASA LaRCNOAA ESRLNaval Research Lab - MontereyJapan’s National Institute of Polar ResearchSpain’s Instituto Nacional de Técnica Aeroespacial - INTA4 US Universities2 Korean Universities1 Taiwan University1 Chinese University other partners pending

Objective: Long-term, local - regional - worldwide aerosol and cloud profile observations using common instrument & data processing in a federated network

active sitesfield campaignsplanned sitesproposed sites

former campaign, permanent site plannedformer campaign, permanent site proposed

* Most sites are co-located with AERONET

* Campaigns utilize SMART-COMMIT and/or

MAARCO platforms

* line denotes research cruise

http://mplnet.gsfc.nasa.gov

Micro-Pulse Lidar Network (MPLNET)

MPLNET Status E.J. Welton, NASA GSFC Code 613.1 04/24/07

Observations of Saharan Dust Transport

Reid et al., JGR, 2003: Puerto Rico Dust Experiment (PRIDE) in 2000

Pink dots indicate Marine Boundary Layer heights from nearby radiosonde

Aerosol & Cloud Extinction Profiles km-1

MPLNET Level 3 Data Cabras Island Site

Ozo

ne (p

pbv)

Using O3-CO Correlations from TES

to Test Model Representation of Ozone Sources

Zhang, Jacob, et al., GRL 2006

Ozone-CO relationshipdownwind of Asia

CO

ppbv

Carbon monoxide (pppbv)

Ozone

Ozo

ne (p

pbv)

TESR=0.38Slope=0.75

GEOS-ChemmodelR=0.79

Slope=0.67

Ozone-CO relationshipdownwind of eastern N. America

ppbv

Carbon monoxide (ppbv)

602 hPa

TES observations, July 2005

Ozo

ne (p

pbv)

TESR=0.64Slope=0.62

GEOS-ChemModelR=0.84

Slope=0.50

Zhang, Jacob, et al., GRL 2006

Ozone-CO relationshipdownwind of Asia

CO

ppbv

Carbon monoxide (pppbv)

Ozone

Ozo

ne (p

pbv)

ppbv

Carbon monoxide (ppbv)

602 hPa

TES observations, July 2005

Using O3-CO Correlations from TES

to Test Model Representation of Ozone Sources

Long-range transport of smoke affects air quality Comparison of MODIS and GOCART

• Pollutants from forest fires (e.g., aerosol particles and ozone) can be transported long distances, affecting surface air quality downwind.

• In July 2004, large forest fires occurred in Alaska and western Canada. Smoke aerosols were transported across Canada and to large areas of continental U.S., affecting regional air quality.

• Event was observed by MODIS and simulated by the GOCART model, which showed a similar pattern and intensity for aerosol optical thickness.

MODIS AOT 550 nm 200407

GOCART AOT 550 nm 200407

Constellation Science

Unique opportunity for conducting Atmospheric Composition science for societal benefit using multiple instruments across international platforms• Collaboration efficiency: take advantage of each instrument’s unique capability

• Cross instrument validation

• Improved spatial and temporal coverage: e.g.different equator crossing times

• Enhanced data products: e.g. aerosol and cloudcharacteristics, pollution and its transport

• More accurate trends by comparing andcombining data sets

A-train is a good example of Constellation Science

CEOS provides an opportunity to extend collaboration internationally

Clouds

Smoke

km-1 sr-1

15

10

5

0

0.000 1.0e-003 0.002 0.003 0.004 0.005 0.006 0.012 0.036 0.072 0.144 0.216 0.400

AIRS Carbon Monoxide CALIPSO clouds and aerosolsPotential Application: Geographic extent of CO from biomass burning in combination with vertical distribution of smoke could improve assessment of totalfire emissions and their downwind transport

Satellites: CALIPSO, Cloudsat, OMI, TES,HIRDLS, MLS, MODIS, AIRS, MISR, MOPITT

• Aerosol optical depth, properties• CO, ozone, NO2

, HCHO, SO2

, BrO

Aircraft: DC-8, WB-57, ER-2, P-3B• Comprehensive in situ chemical and aerosol

measurements• Passive remote sensing of aerosol impacts

on radiation• Active remote sensing of ozone and aerosol

optical properties

Models: CTMs, GCMs, ESMs• Source-receptor relationships for pollution• Inverse modeling for estimating emissions• Aerosol radiative

forcing• Detailed chemical processing

Data assimilationDiagnostic studies

Retrieval algorithm development& validation

Correlative informationModel error characterization

Airborne Field Campaign Strategy: Use aircraft to increase Airborne Field Campaign Strategy: Use aircraft to increase the value of satellite data for improving models of the value of satellite data for improving models of

atmospheric composition and climate.atmospheric composition and climate.

WCRP-SPARC/IGBP-IGAC Atmospheric Chemistry and Climate Initiative

“Tropos Chem”(tropospheric gas-

phase chem)

CCM-Val (stratospheric gas- phase chemistry)

AC&C Research Activities

AEROCOM(tropospheric

aerosols)

Research Implementation Bodies

1) Emissions Harmonization Committee2) Data Center Committee3) AC&C Web page & “E- newsletter”

Overarching Activities

Unifying thematic areasComposition impacts on climateClimate impacts on chemistryClimate impacts on surface-level ozone & aerosols (“air quality”)

1) 20 year hindcast for tropospheric gases/aerosols2) What controls the distribution of tropospheric aerosols/gases? (Step 1: Focus on 5km to tropopause distribution)3) Cloud/aerosol/chemical interactions4) Future scenarios; sensitivities & uncertainties

> Motivated but not funded by “international” organizations> The success of these activities is contingent on buy-in from the scientific

community, including us> By participating, we take advantage of the community as well

– Share progresses on model improvement and development– Better evaluate the model performance– Better access to emission, observations, etc.– More relevant to international community

>The ensemble of model results are proven to be more robust than a single “best” model (if there is any). Therefore, these exercises can be used for

– Analyzing data from past and current missions to better understand global and regional aerosol trends, emissions, processes, and impacts

– Identifying common needs or problems among the models that can be used to recommend or emphasize future observation priorities

– Forming an international assessment body (e.g., IPCC, WMO, CCSP) providing guidance for research and policies